Overview

Dataset statistics

Number of variables24
Number of observations92328
Missing cells21
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 MiB
Average record size in memory192.0 B

Variable types

Numeric22
Categorical2

Alerts

title has a high cardinality: 43982 distinct valuesHigh cardinality
artist has a high cardinality: 17548 distinct valuesHigh cardinality
admiration is highly overall correlated with prideHigh correlation
anger is highly overall correlated with confusion and 5 other fieldsHigh correlation
caring is highly overall correlated with optimism and 1 other fieldsHigh correlation
confusion is highly overall correlated with anger and 6 other fieldsHigh correlation
desire is highly overall correlated with optimismHigh correlation
disappointment is highly overall correlated with anger and 6 other fieldsHigh correlation
disapproval is highly overall correlated with anger and 6 other fieldsHigh correlation
embarrassment is highly overall correlated with anger and 6 other fieldsHigh correlation
excitement is highly overall correlated with joy and 1 other fieldsHigh correlation
fear is highly overall correlated with anger and 6 other fieldsHigh correlation
joy is highly overall correlated with excitement and 1 other fieldsHigh correlation
optimism is highly overall correlated with caring and 1 other fieldsHigh correlation
pride is highly overall correlated with admiration and 1 other fieldsHigh correlation
realization is highly overall correlated with confusion and 5 other fieldsHigh correlation
relief is highly overall correlated with caring and 1 other fieldsHigh correlation
sadness is highly overall correlated with anger and 6 other fieldsHigh correlation
embarrassment is highly skewed (γ1 = 42.45587792)Skewed
Unnamed: 0 is uniformly distributedUniform
Unnamed: 0 has unique valuesUnique

Reproduction

Analysis started2023-07-10 05:22:46.310900
Analysis finished2023-07-10 05:23:23.765374
Duration37.45 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct92328
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46163.5
Minimum0
Maximum92327
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:23.823795image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4616.35
Q123081.75
median46163.5
Q369245.25
95-th percentile87710.65
Maximum92327
Range92327
Interquartile range (IQR)46163.5

Descriptive statistics

Standard deviation26652.942
Coefficient of variation (CV)0.57735965
Kurtosis-1.2
Mean46163.5
Median Absolute Deviation (MAD)23082
Skewness0
Sum4.2621836 × 109
Variance7.1037933 × 108
MonotonicityStrictly increasing
2023-07-10T14:23:24.011639image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
< 0.1%
61558 1
 
< 0.1%
61556 1
 
< 0.1%
61555 1
 
< 0.1%
61554 1
 
< 0.1%
61553 1
 
< 0.1%
61552 1
 
< 0.1%
61551 1
 
< 0.1%
61550 1
 
< 0.1%
61549 1
 
< 0.1%
Other values (92318) 92318
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
ValueCountFrequency (%)
92327 1
< 0.1%
92326 1
< 0.1%
92325 1
< 0.1%
92324 1
< 0.1%
92323 1
< 0.1%
92322 1
< 0.1%
92321 1
< 0.1%
92320 1
< 0.1%
92319 1
< 0.1%
92318 1
< 0.1%

title
Categorical

Distinct43982
Distinct (%)47.6%
Missing0
Missing (%)0.0%
Memory size721.4 KiB
고백
 
195
괜찮아
 
99
위로
 
99
좋아해
 
65
수고했어, 오늘도
 
63
Other values (43977)
91807 

Length

Max length202
Median length149
Mean length14.362544
Min length1

Characters and Unicode

Total characters1326065
Distinct characters2038
Distinct categories20 ?
Distinct scripts7 ?
Distinct blocks18 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28624 ?
Unique (%)31.0%

Sample

1st row행복
2nd rowSweety
3rd row커피 한잔 어때? (feat. 요조)
4th row기분 좋은 상상
5th row좋아요~

Common Values

ValueCountFrequency (%)
고백 195
 
0.2%
괜찮아 99
 
0.1%
위로 99
 
0.1%
좋아해 65
 
0.1%
수고했어, 오늘도 63
 
0.1%
Home 62
 
0.1%
청춘 60
 
0.1%
사랑해 60
 
0.1%
I Love You 56
 
0.1%
피아노 포엠(Piano Poem) 55
 
0.1%
Other values (43972) 91514
99.1%

Length

2023-07-10T14:23:24.094913image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
feat 12728
 
4.5%
you 4099
 
1.5%
love 3576
 
1.3%
the 3532
 
1.3%
of 2948
 
1.0%
with 2440
 
0.9%
2412
 
0.9%
i 2273
 
0.8%
me 2207
 
0.8%
in 1588
 
0.6%
Other values (34105) 243891
86.6%

Most occurring characters

ValueCountFrequency (%)
189693
 
14.3%
e 83492
 
6.3%
a 55485
 
4.2%
o 52686
 
4.0%
t 45760
 
3.5%
i 42877
 
3.2%
n 38619
 
2.9%
r 34713
 
2.6%
( 30625
 
2.3%
) 30620
 
2.3%
Other values (2028) 721495
54.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 567205
42.8%
Other Letter 297930
22.5%
Space Separator 189826
 
14.3%
Uppercase Letter 162759
 
12.3%
Other Punctuation 34962
 
2.6%
Open Punctuation 30825
 
2.3%
Close Punctuation 30782
 
2.3%
Decimal Number 9488
 
0.7%
Dash Punctuation 1683
 
0.1%
Math Symbol 175
 
< 0.1%
Other values (10) 430
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9260
 
3.1%
5963
 
2.0%
5774
 
1.9%
5462
 
1.8%
4787
 
1.6%
4765
 
1.6%
4680
 
1.6%
4537
 
1.5%
4465
 
1.5%
4283
 
1.4%
Other values (1847) 243954
81.9%
Lowercase Letter
ValueCountFrequency (%)
e 83492
14.7%
a 55485
 
9.8%
o 52686
 
9.3%
t 45760
 
8.1%
i 42877
 
7.6%
n 38619
 
6.8%
r 34713
 
6.1%
l 26434
 
4.7%
s 22865
 
4.0%
u 20765
 
3.7%
Other values (51) 143509
25.3%
Uppercase Letter
ValueCountFrequency (%)
S 12840
 
7.9%
M 11452
 
7.0%
T 11397
 
7.0%
L 10778
 
6.6%
B 9639
 
5.9%
A 9626
 
5.9%
O 8389
 
5.2%
I 8371
 
5.1%
W 7701
 
4.7%
R 7543
 
4.6%
Other values (28) 65023
40.0%
Other Punctuation
ValueCountFrequency (%)
. 20360
58.2%
' 4927
 
14.1%
, 4506
 
12.9%
& 1410
 
4.0%
: 1263
 
3.6%
! 802
 
2.3%
? 623
 
1.8%
" 498
 
1.4%
/ 324
 
0.9%
# 80
 
0.2%
Other values (14) 169
 
0.5%
Other Symbol
ValueCountFrequency (%)
39
38.2%
21
20.6%
7
 
6.9%
7
 
6.9%
6
 
5.9%
6
 
5.9%
6
 
5.9%
° 5
 
4.9%
® 3
 
2.9%
1
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 2207
23.3%
2 1800
19.0%
0 1478
15.6%
3 834
 
8.8%
4 713
 
7.5%
9 641
 
6.8%
5 526
 
5.5%
7 483
 
5.1%
6 417
 
4.4%
8 389
 
4.1%
Math Symbol
ValueCountFrequency (%)
+ 72
41.1%
~ 50
28.6%
= 28
 
16.0%
< 10
 
5.7%
> 9
 
5.1%
2
 
1.1%
2
 
1.1%
2
 
1.1%
Open Punctuation
ValueCountFrequency (%)
( 30625
99.4%
[ 158
 
0.5%
38
 
0.1%
3
 
< 0.1%
{ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 30620
99.5%
] 158
 
0.5%
3
 
< 0.1%
} 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
13
72.2%
3
 
16.7%
1
 
5.6%
1
 
5.6%
Modifier Symbol
ValueCountFrequency (%)
^ 4
50.0%
´ 3
37.5%
˚ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
189693
99.9%
  133
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1680
99.8%
3
 
0.2%
Final Punctuation
ValueCountFrequency (%)
164
97.6%
4
 
2.4%
Initial Punctuation
ValueCountFrequency (%)
25
89.3%
3
 
10.7%
Currency Symbol
ValueCountFrequency (%)
$ 73
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 22
100.0%
Modifier Letter
ValueCountFrequency (%)
7
100.0%
Control
ValueCountFrequency (%)
’ 2
100.0%
Other Number
ValueCountFrequency (%)
² 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 729975
55.0%
Common 298153
22.5%
Hangul 295891
22.3%
Han 1370
 
0.1%
Hiragana 441
 
< 0.1%
Katakana 228
 
< 0.1%
Cyrillic 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9260
 
3.1%
5963
 
2.0%
5774
 
2.0%
5462
 
1.8%
4787
 
1.6%
4765
 
1.6%
4680
 
1.6%
4537
 
1.5%
4465
 
1.5%
4283
 
1.4%
Other values (1325) 241915
81.8%
Han
ValueCountFrequency (%)
53
 
3.9%
40
 
2.9%
28
 
2.0%
27
 
2.0%
24
 
1.8%
23
 
1.7%
23
 
1.7%
20
 
1.5%
18
 
1.3%
17
 
1.2%
Other values (397) 1097
80.1%
Latin
ValueCountFrequency (%)
e 83492
 
11.4%
a 55485
 
7.6%
o 52686
 
7.2%
t 45760
 
6.3%
i 42877
 
5.9%
n 38619
 
5.3%
r 34713
 
4.8%
l 26434
 
3.6%
s 22865
 
3.1%
u 20765
 
2.8%
Other values (87) 306279
42.0%
Common
ValueCountFrequency (%)
189693
63.6%
( 30625
 
10.3%
) 30620
 
10.3%
. 20360
 
6.8%
' 4927
 
1.7%
, 4506
 
1.5%
1 2207
 
0.7%
2 1800
 
0.6%
- 1680
 
0.6%
0 1478
 
0.5%
Other values (68) 10257
 
3.4%
Katakana
ValueCountFrequency (%)
19
 
8.3%
13
 
5.7%
13
 
5.7%
11
 
4.8%
11
 
4.8%
9
 
3.9%
9
 
3.9%
8
 
3.5%
8
 
3.5%
7
 
3.1%
Other values (48) 120
52.6%
Hiragana
ValueCountFrequency (%)
63
 
14.3%
34
 
7.7%
28
 
6.3%
17
 
3.9%
16
 
3.6%
13
 
2.9%
13
 
2.9%
13
 
2.9%
12
 
2.7%
12
 
2.7%
Other values (47) 220
49.9%
Cyrillic
ValueCountFrequency (%)
а 2
28.6%
н 1
14.3%
и 1
14.3%
р 1
14.3%
б 1
14.3%
С 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1027278
77.5%
Hangul 295837
 
22.3%
CJK 1302
 
0.1%
None 474
 
< 0.1%
Hiragana 441
 
< 0.1%
Punctuation 248
 
< 0.1%
Katakana 239
 
< 0.1%
CJK Compat Ideographs 67
 
< 0.1%
Misc Symbols 59
 
< 0.1%
Compat Jamo 37
 
< 0.1%
Other values (8) 83
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189693
18.5%
e 83492
 
8.1%
a 55485
 
5.4%
o 52686
 
5.1%
t 45760
 
4.5%
i 42877
 
4.2%
n 38619
 
3.8%
r 34713
 
3.4%
( 30625
 
3.0%
) 30620
 
3.0%
Other values (83) 422708
41.1%
Hangul
ValueCountFrequency (%)
9260
 
3.1%
5963
 
2.0%
5774
 
2.0%
5462
 
1.8%
4787
 
1.6%
4765
 
1.6%
4680
 
1.6%
4537
 
1.5%
4465
 
1.5%
4283
 
1.4%
Other values (1302) 241861
81.8%
Punctuation
ValueCountFrequency (%)
164
66.1%
38
 
15.3%
25
 
10.1%
6
 
2.4%
5
 
2.0%
4
 
1.6%
3
 
1.2%
3
 
1.2%
None
ValueCountFrequency (%)
  133
28.1%
é 90
19.0%
á 31
 
6.5%
Ø 19
 
4.0%
ó 11
 
2.3%
ä 11
 
2.3%
ë 10
 
2.1%
í 10
 
2.1%
É 10
 
2.1%
ñ 9
 
1.9%
Other values (46) 140
29.5%
Hiragana
ValueCountFrequency (%)
63
 
14.3%
34
 
7.7%
28
 
6.3%
17
 
3.9%
16
 
3.6%
13
 
2.9%
13
 
2.9%
13
 
2.9%
12
 
2.7%
12
 
2.7%
Other values (47) 220
49.9%
CJK
ValueCountFrequency (%)
53
 
4.1%
40
 
3.1%
28
 
2.2%
27
 
2.1%
24
 
1.8%
23
 
1.8%
23
 
1.8%
20
 
1.5%
18
 
1.4%
17
 
1.3%
Other values (378) 1029
79.0%
Misc Symbols
ValueCountFrequency (%)
39
66.1%
7
 
11.9%
6
 
10.2%
6
 
10.2%
1
 
1.7%
Geometric Shapes
ValueCountFrequency (%)
21
77.8%
6
 
22.2%
Katakana
ValueCountFrequency (%)
19
 
7.9%
13
 
5.4%
13
 
5.4%
11
 
4.6%
11
 
4.6%
9
 
3.8%
9
 
3.8%
8
 
3.3%
8
 
3.3%
7
 
2.9%
Other values (50) 131
54.8%
CJK Compat Ideographs
ValueCountFrequency (%)
13
19.4%
9
13.4%
8
11.9%
6
9.0%
5
 
7.5%
4
 
6.0%
4
 
6.0%
3
 
4.5%
3
 
4.5%
3
 
4.5%
Other values (8) 9
13.4%
Number Forms
ValueCountFrequency (%)
13
72.2%
3
 
16.7%
1
 
5.6%
1
 
5.6%
Compat Jamo
ValueCountFrequency (%)
10
27.0%
8
21.6%
4
 
10.8%
3
 
8.1%
3
 
8.1%
2
 
5.4%
2
 
5.4%
2
 
5.4%
1
 
2.7%
1
 
2.7%
Letterlike Symbols
ValueCountFrequency (%)
7
87.5%
1
 
12.5%
Jamo
ValueCountFrequency (%)
3
17.6%
2
11.8%
2
11.8%
2
11.8%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
1
 
5.9%
Other values (2) 2
11.8%
Cyrillic
ValueCountFrequency (%)
а 2
28.6%
н 1
14.3%
и 1
14.3%
р 1
14.3%
б 1
14.3%
С 1
14.3%
Math Operators
ValueCountFrequency (%)
2
50.0%
2
50.0%
Modifier Letters
ValueCountFrequency (%)
˚ 1
100.0%
CJK Ext A
ValueCountFrequency (%)
1
100.0%

artist
Categorical

Distinct17548
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size721.4 KiB
아이유(IU)
 
534
성시경
 
453
윤종신
 
374
스탠딩 에그(Standing Egg)
 
366
윤하(Younha/ユンナ)
 
345
Other values (17543)
90256 

Length

Max length159
Median length76
Mean length11.464864
Min length1

Characters and Unicode

Total characters1058528
Distinct characters1622
Distinct categories17 ?
Distinct scripts8 ?
Distinct blocks11 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9546 ?
Unique (%)10.3%

Sample

1st rowSUPER JUNIOR (슈퍼주니어)
2nd row클래지콰이(Clazziquai)
3rd rowHUS(허밍어반스테레오)
4th row여행스케치
5th row불독맨션(Bulldogmansion)

Common Values

ValueCountFrequency (%)
아이유(IU) 534
 
0.6%
성시경 453
 
0.5%
윤종신 374
 
0.4%
스탠딩 에그(Standing Egg) 366
 
0.4%
윤하(Younha/ユンナ) 345
 
0.4%
어반자카파 342
 
0.4%
김동률 323
 
0.3%
10CM 305
 
0.3%
제이레빗(J Rabbit) 275
 
0.3%
옥상달빛 272
 
0.3%
Other values (17538) 88739
96.1%

Length

2023-07-10T14:23:24.187104image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the 2040
 
1.2%
1232
 
0.7%
616
 
0.4%
아이유(iu 534
 
0.3%
project 497
 
0.3%
성시경 453
 
0.3%
kim 410
 
0.2%
윤종신 374
 
0.2%
of 374
 
0.2%
브라운 371
 
0.2%
Other values (24528) 160716
95.9%

Most occurring characters

ValueCountFrequency (%)
75170
 
7.1%
( 54063
 
5.1%
) 54063
 
5.1%
e 47407
 
4.5%
a 43001
 
4.1%
o 34408
 
3.3%
i 33951
 
3.2%
n 32693
 
3.1%
r 27212
 
2.6%
l 23760
 
2.2%
Other values (1612) 632800
59.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 391417
37.0%
Other Letter 315188
29.8%
Uppercase Letter 153536
 
14.5%
Space Separator 75290
 
7.1%
Open Punctuation 54170
 
5.1%
Close Punctuation 54170
 
5.1%
Other Punctuation 6998
 
0.7%
Decimal Number 5897
 
0.6%
Dash Punctuation 1245
 
0.1%
Control 290
 
< 0.1%
Other values (7) 327
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
18317
 
5.8%
15085
 
4.8%
8033
 
2.5%
6104
 
1.9%
5438
 
1.7%
4830
 
1.5%
4489
 
1.4%
4436
 
1.4%
3444
 
1.1%
3437
 
1.1%
Other values (1459) 241575
76.6%
Lowercase Letter
ValueCountFrequency (%)
e 47407
12.1%
a 43001
11.0%
o 34408
 
8.8%
i 33951
 
8.7%
n 32693
 
8.4%
r 27212
 
7.0%
l 23760
 
6.1%
t 19828
 
5.1%
s 19219
 
4.9%
u 14397
 
3.7%
Other values (57) 95541
24.4%
Uppercase Letter
ValueCountFrequency (%)
S 12528
 
8.2%
M 9952
 
6.5%
E 9627
 
6.3%
A 9410
 
6.1%
T 8788
 
5.7%
C 8663
 
5.6%
B 8126
 
5.3%
R 7659
 
5.0%
N 7559
 
4.9%
L 7244
 
4.7%
Other values (27) 63980
41.7%
Other Punctuation
ValueCountFrequency (%)
. 3215
45.9%
& 1097
 
15.7%
' 896
 
12.8%
/ 867
 
12.4%
! 306
 
4.4%
, 295
 
4.2%
: 206
 
2.9%
# 44
 
0.6%
% 19
 
0.3%
* 12
 
0.2%
Other values (6) 41
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 1487
25.2%
0 851
14.4%
2 840
14.2%
4 735
12.5%
5 563
 
9.5%
3 351
 
6.0%
9 326
 
5.5%
6 266
 
4.5%
7 257
 
4.4%
8 221
 
3.7%
Math Symbol
ValueCountFrequency (%)
+ 33
36.3%
> 22
24.2%
< 22
24.2%
~ 9
 
9.9%
= 5
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 1241
99.7%
3
 
0.2%
1
 
0.1%
Space Separator
ValueCountFrequency (%)
75170
99.8%
  120
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 54063
99.8%
[ 107
 
0.2%
Close Punctuation
ValueCountFrequency (%)
) 54063
99.8%
] 107
 
0.2%
Modifier Symbol
ValueCountFrequency (%)
^ 45
95.7%
` 2
 
4.3%
Other Symbol
ValueCountFrequency (%)
29
96.7%
1
 
3.3%
Control
ValueCountFrequency (%)
290
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 109
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 42
100.0%
Modifier Letter
ValueCountFrequency (%)
7
100.0%
Format
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 544940
51.5%
Hangul 311963
29.5%
Common 198387
 
18.7%
Katakana 1717
 
0.2%
Han 1436
 
0.1%
Hiragana 72
 
< 0.1%
Cyrillic 11
 
< 0.1%
Greek 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
18317
 
5.9%
15085
 
4.8%
8033
 
2.6%
6104
 
2.0%
5438
 
1.7%
4830
 
1.5%
4489
 
1.4%
4436
 
1.4%
3444
 
1.1%
3437
 
1.1%
Other values (1067) 238350
76.4%
Han
ValueCountFrequency (%)
77
 
5.4%
65
 
4.5%
63
 
4.4%
62
 
4.3%
45
 
3.1%
43
 
3.0%
32
 
2.2%
30
 
2.1%
28
 
1.9%
27
 
1.9%
Other values (293) 964
67.1%
Latin
ValueCountFrequency (%)
e 47407
 
8.7%
a 43001
 
7.9%
o 34408
 
6.3%
i 33951
 
6.2%
n 32693
 
6.0%
r 27212
 
5.0%
l 23760
 
4.4%
t 19828
 
3.6%
s 19219
 
3.5%
u 14397
 
2.6%
Other values (84) 249064
45.7%
Katakana
ValueCountFrequency (%)
381
22.2%
348
20.3%
346
20.2%
133
 
7.7%
54
 
3.1%
48
 
2.8%
46
 
2.7%
29
 
1.7%
23
 
1.3%
21
 
1.2%
Other values (49) 288
16.8%
Common
ValueCountFrequency (%)
75170
37.9%
( 54063
27.3%
) 54063
27.3%
. 3215
 
1.6%
1 1487
 
0.7%
- 1241
 
0.6%
& 1097
 
0.6%
' 896
 
0.5%
/ 867
 
0.4%
0 851
 
0.4%
Other values (39) 5437
 
2.7%
Hiragana
ValueCountFrequency (%)
8
 
11.1%
6
 
8.3%
6
 
8.3%
5
 
6.9%
4
 
5.6%
4
 
5.6%
4
 
5.6%
3
 
4.2%
3
 
4.2%
2
 
2.8%
Other values (20) 27
37.5%
Cyrillic
ValueCountFrequency (%)
о 3
27.3%
е 1
 
9.1%
н 1
 
9.1%
г 1
 
9.1%
т 1
 
9.1%
Э 1
 
9.1%
б 1
 
9.1%
ы 1
 
9.1%
л 1
 
9.1%
Greek
ValueCountFrequency (%)
α 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 742682
70.2%
Hangul 311953
29.5%
Katakana 1724
 
0.2%
CJK 1414
 
0.1%
None 605
 
0.1%
Hiragana 72
 
< 0.1%
Misc Symbols 30
 
< 0.1%
CJK Compat Ideographs 22
 
< 0.1%
Cyrillic 11
 
< 0.1%
Compat Jamo 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
75170
 
10.1%
( 54063
 
7.3%
) 54063
 
7.3%
e 47407
 
6.4%
a 43001
 
5.8%
o 34408
 
4.6%
i 33951
 
4.6%
n 32693
 
4.4%
r 27212
 
3.7%
l 23760
 
3.2%
Other values (82) 316954
42.7%
Hangul
ValueCountFrequency (%)
18317
 
5.9%
15085
 
4.8%
8033
 
2.6%
6104
 
2.0%
5438
 
1.7%
4830
 
1.5%
4489
 
1.4%
4436
 
1.4%
3444
 
1.1%
3437
 
1.1%
Other values (1065) 238340
76.4%
Katakana
ValueCountFrequency (%)
381
22.1%
348
20.2%
346
20.1%
133
 
7.7%
54
 
3.1%
48
 
2.8%
46
 
2.7%
29
 
1.7%
23
 
1.3%
21
 
1.2%
Other values (50) 295
17.1%
None
ValueCountFrequency (%)
é 219
36.2%
  120
19.8%
Ø 67
 
11.1%
ö 29
 
4.8%
ü 20
 
3.3%
ø 17
 
2.8%
Ü 16
 
2.6%
á 11
 
1.8%
É 11
 
1.8%
ó 9
 
1.5%
Other values (36) 86
 
14.2%
CJK
ValueCountFrequency (%)
77
 
5.4%
65
 
4.6%
63
 
4.5%
62
 
4.4%
45
 
3.2%
43
 
3.0%
32
 
2.3%
30
 
2.1%
28
 
2.0%
27
 
1.9%
Other values (288) 942
66.6%
Misc Symbols
ValueCountFrequency (%)
29
96.7%
1
 
3.3%
CJK Compat Ideographs
ValueCountFrequency (%)
16
72.7%
3
 
13.6%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Hiragana
ValueCountFrequency (%)
8
 
11.1%
6
 
8.3%
6
 
8.3%
5
 
6.9%
4
 
5.6%
4
 
5.6%
4
 
5.6%
3
 
4.2%
3
 
4.2%
2
 
2.8%
Other values (20) 27
37.5%
Compat Jamo
ValueCountFrequency (%)
7
70.0%
3
30.0%
Cyrillic
ValueCountFrequency (%)
о 3
27.3%
е 1
 
9.1%
н 1
 
9.1%
г 1
 
9.1%
т 1
 
9.1%
Э 1
 
9.1%
б 1
 
9.1%
ы 1
 
9.1%
л 1
 
9.1%
Punctuation
ValueCountFrequency (%)
3
60.0%
1
 
20.0%
1
 
20.0%

admiration
Real number (ℝ)

Distinct4727
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.24650986
Minimum0.00082577042
Maximum1.3909265
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:24.277746image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00082577042
5-th percentile0.0052146602
Q10.018501339
median0.077223659
Q30.38754324
95-th percentile0.96722499
Maximum1.3909265
Range1.3901008
Interquartile range (IQR)0.3690419

Descriptive statistics

Standard deviation0.32151487
Coefficient of variation (CV)1.3042678
Kurtosis0.11155855
Mean0.24650986
Median Absolute Deviation (MAD)0.067883041
Skewness1.2675535
Sum22759.516
Variance0.10337181
MonotonicityNot monotonic
2023-07-10T14:23:24.355653image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1174636626 2809
 
3.0%
0.1924836384 100
 
0.1%
0.2400888824 100
 
0.1%
0.01444414398 100
 
0.1%
0.03763104952 97
 
0.1%
0.2188613564 97
 
0.1%
0.8226835597 97
 
0.1%
0.02641631057 96
 
0.1%
0.391176569 95
 
0.1%
0.1616063279 89
 
0.1%
Other values (4717) 88647
96.0%
ValueCountFrequency (%)
0.0008257704176 15
< 0.1%
0.001034484521 19
< 0.1%
0.001194724784 18
< 0.1%
0.00120643439 25
< 0.1%
0.001333650027 15
< 0.1%
0.001506396366 20
< 0.1%
0.001667496166 20
< 0.1%
0.001732979377 19
< 0.1%
0.001775559445 25
< 0.1%
0.001786104054 9
 
< 0.1%
ValueCountFrequency (%)
1.39092654 10
 
< 0.1%
1.242957979 20
< 0.1%
1.084393144 15
< 0.1%
1.079527915 14
< 0.1%
1.064499706 18
< 0.1%
1.064216323 15
< 0.1%
1.054949544 20
< 0.1%
1.047249645 20
< 0.1%
1.038826957 30
< 0.1%
1.03400214 13
< 0.1%

anger
Real number (ℝ)

Distinct4727
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.011990749
Minimum0.00064155241
Maximum1.2761064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:24.437290image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00064155241
5-th percentile0.001493785
Q10.0033578392
median0.0055788321
Q30.0098027042
95-th percentile0.027842827
Maximum1.2761064
Range1.2754648
Interquartile range (IQR)0.006444865

Descriptive statistics

Standard deviation0.042964313
Coefficient of variation (CV)3.5831218
Kurtosis439.2302
Mean0.011990749
Median Absolute Deviation (MAD)0.002719062
Skewness18.309616
Sum1107.0699
Variance0.0018459322
MonotonicityNot monotonic
2023-07-10T14:23:24.520369image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001292388391 2809
 
3.0%
0.003958837013 100
 
0.1%
0.002726221399 100
 
0.1%
0.01702477457 100
 
0.1%
0.00363690732 97
 
0.1%
0.003063945798 97
 
0.1%
0.001454092009 97
 
0.1%
0.008161334204 96
 
0.1%
0.001602826145 95
 
0.1%
0.00417650718 89
 
0.1%
Other values (4717) 88647
96.0%
ValueCountFrequency (%)
0.0006415524113 21
 
< 0.1%
0.0009190803976 14
 
< 0.1%
0.0009350489272 16
 
< 0.1%
0.0009966371726 20
 
< 0.1%
0.0009994395077 15
 
< 0.1%
0.001032746397 19
 
< 0.1%
0.001043243363 29
< 0.1%
0.001057495756 63
0.1%
0.001080946444 15
 
< 0.1%
0.001081670387 11
 
< 0.1%
ValueCountFrequency (%)
1.27610638 29
< 0.1%
1.09886955 20
< 0.1%
1.027433604 20
< 0.1%
0.8769451762 14
< 0.1%
0.5756419078 20
< 0.1%
0.5585460709 15
< 0.1%
0.5203245282 15
< 0.1%
0.517764857 10
 
< 0.1%
0.4826241005 15
< 0.1%
0.4046703787 17
< 0.1%

approval
Real number (ℝ)

Distinct4726
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.10922869
Minimum0.00071990921
Maximum0.98013639
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:24.611226image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00071990921
5-th percentile0.0056303637
Q10.017088978
median0.039507508
Q30.10625861
95-th percentile0.51704586
Maximum0.98013639
Range0.97941649
Interquartile range (IQR)0.089169631

Descriptive statistics

Standard deviation0.17545994
Coefficient of variation (CV)1.606354
Kurtosis7.7128693
Mean0.10922869
Median Absolute Deviation (MAD)0.026851565
Skewness2.7665926
Sum10084.757
Variance0.03078619
MonotonicityNot monotonic
2023-07-10T14:23:24.687373image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01698132977 2809
 
3.0%
0.06090920046 100
 
0.1%
0.05008746684 100
 
0.1%
0.01214810833 100
 
0.1%
0.07413957268 97
 
0.1%
0.1805834621 97
 
0.1%
0.9133541584 97
 
0.1%
0.012373548 96
 
0.1%
0.8344758749 95
 
0.1%
0.4316218197 89
 
0.1%
Other values (4716) 88647
96.0%
ValueCountFrequency (%)
0.000719909207 18
< 0.1%
0.0007248958573 17
< 0.1%
0.0007425923832 15
< 0.1%
0.0009473333484 17
< 0.1%
0.0009870148497 20
< 0.1%
0.0009985188954 20
< 0.1%
0.001075161737 20
< 0.1%
0.001081800787 15
< 0.1%
0.001094746287 20
< 0.1%
0.001101304195 20
< 0.1%
ValueCountFrequency (%)
0.9801363945 20
< 0.1%
0.9738334417 30
< 0.1%
0.9726104736 20
< 0.1%
0.9588727355 17
< 0.1%
0.9588271379 15
< 0.1%
0.9548637867 17
< 0.1%
0.9533193707 20
< 0.1%
0.9481939077 25
< 0.1%
0.940284729 20
< 0.1%
0.9396053553 10
 
< 0.1%

caring
Real number (ℝ)

Distinct4727
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.17494835
Minimum0.00012540063
Maximum0.98370266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:24.762931image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00012540063
5-th percentile0.0011683077
Q10.011350531
median0.048131723
Q30.21475156
95-th percentile0.82779109
Maximum0.98370266
Range0.98357726
Interquartile range (IQR)0.20340103

Descriptive statistics

Standard deviation0.25685922
Coefficient of variation (CV)1.4682003
Kurtosis1.7778484
Mean0.17494835
Median Absolute Deviation (MAD)0.044285662
Skewness1.71915
Sum16152.456
Variance0.065976657
MonotonicityNot monotonic
2023-07-10T14:23:24.838191image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.000461006508 2809
 
3.0%
0.2700811923 100
 
0.1%
0.05948157981 100
 
0.1%
0.04813172296 100
 
0.1%
0.01194346137 97
 
0.1%
0.00371643831 97
 
0.1%
0.02456378005 97
 
0.1%
0.00488705188 96
 
0.1%
0.08024975657 95
 
0.1%
0.191168353 89
 
0.1%
Other values (4717) 88647
96.0%
ValueCountFrequency (%)
0.0001254006347 15
 
< 0.1%
0.0002112791262 20
 
< 0.1%
0.0002165979386 52
0.1%
0.0002211144892 19
 
< 0.1%
0.0002283267968 19
 
< 0.1%
0.0002991468064 14
 
< 0.1%
0.0002998000709 20
 
< 0.1%
0.0003088741505 20
 
< 0.1%
0.0003127935051 19
 
< 0.1%
0.000322285603 29
< 0.1%
ValueCountFrequency (%)
0.9837026596 15
< 0.1%
0.9801505804 14
< 0.1%
0.9798133373 17
< 0.1%
0.9778026342 18
< 0.1%
0.9766759276 30
< 0.1%
0.9737288952 20
< 0.1%
0.9722316265 15
< 0.1%
0.9717798829 20
< 0.1%
0.9709100127 15
< 0.1%
0.9708239436 21
< 0.1%

confusion
Real number (ℝ)

Distinct4727
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.061141645
Minimum0.00054257114
Maximum1.116802
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:24.912597image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00054257114
5-th percentile0.0015248765
Q10.0051260556
median0.01466256
Q30.048493285
95-th percentile0.30797129
Maximum1.116802
Range1.1162594
Interquartile range (IQR)0.04336723

Descriptive statistics

Standard deviation0.13097463
Coefficient of variation (CV)2.1421509
Kurtosis18.404961
Mean0.061141645
Median Absolute Deviation (MAD)0.011816261
Skewness3.9930721
Sum5645.0246
Variance0.017154354
MonotonicityNot monotonic
2023-07-10T14:23:24.985678image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001264776904 2809
 
3.0%
0.01313554076 100
 
0.1%
0.01015535928 100
 
0.1%
0.07090305351 100
 
0.1%
0.00514150376 97
 
0.1%
0.001639769238 97
 
0.1%
0.007298569661 97
 
0.1%
0.005513132783 96
 
0.1%
0.007529373746 95
 
0.1%
0.01967079658 89
 
0.1%
Other values (4717) 88647
96.0%
ValueCountFrequency (%)
0.0005425711424 15
< 0.1%
0.0006028730859 17
< 0.1%
0.0007095576148 15
< 0.1%
0.000716888695 20
< 0.1%
0.0007679236878 25
< 0.1%
0.0008204655896 20
< 0.1%
0.000820624351 25
< 0.1%
0.0009414775413 20
< 0.1%
0.0009415403474 22
< 0.1%
0.0009614281735 15
< 0.1%
ValueCountFrequency (%)
1.116801977 20
< 0.1%
1.02629678 20
< 0.1%
0.9951417223 13
< 0.1%
0.9883887209 25
< 0.1%
0.9825485128 18
< 0.1%
0.9758014083 15
< 0.1%
0.9753960677 20
< 0.1%
0.9455992281 16
< 0.1%
0.9427540759 15
< 0.1%
0.9417545944 28
< 0.1%

curiosity
Real number (ℝ)

Distinct4725
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.027524712
Minimum0.00014012025
Maximum0.97665477
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:25.059771image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00014012025
5-th percentile0.0007819974
Q10.001748126
median0.0037380278
Q30.0099869734
95-th percentile0.12230399
Maximum0.97665477
Range0.97651465
Interquartile range (IQR)0.0082388474

Descriptive statistics

Standard deviation0.097196394
Coefficient of variation (CV)3.5312411
Kurtosis44.001168
Mean0.027524712
Median Absolute Deviation (MAD)0.0025376793
Skewness6.2320634
Sum2541.2741
Variance0.0094471389
MonotonicityNot monotonic
2023-07-10T14:23:25.130229image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0008984494489 2809
 
3.0%
0.976654768 100
 
0.1%
0.09991198778 100
 
0.1%
0.1280589849 100
 
0.1%
0.04278175533 97
 
0.1%
0.001946272678 97
 
0.1%
0.001321340096 97
 
0.1%
0.01475295518 96
 
0.1%
0.001952008926 95
 
0.1%
0.003134171478 89
 
0.1%
Other values (4715) 88647
96.0%
ValueCountFrequency (%)
0.0001401202462 11
< 0.1%
0.0001546474232 17
< 0.1%
0.0001638053072 20
< 0.1%
0.0001854305592 20
< 0.1%
0.0001981037203 19
< 0.1%
0.000204130527 15
< 0.1%
0.000231945698 18
< 0.1%
0.0002548943739 20
< 0.1%
0.0002550696372 10
< 0.1%
0.0002665876527 16
< 0.1%
ValueCountFrequency (%)
0.976654768 100
0.1%
0.9631661773 17
 
< 0.1%
0.9475915432 20
 
< 0.1%
0.9373162389 15
 
< 0.1%
0.929484129 13
 
< 0.1%
0.928453505 15
 
< 0.1%
0.9252541661 20
 
< 0.1%
0.9225245714 20
 
< 0.1%
0.9195581675 19
 
< 0.1%
0.8868913651 20
 
< 0.1%

desire
Real number (ℝ)

Distinct4726
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.03076342
Minimum0.00022221328
Maximum0.9574104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:25.201773image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00022221328
5-th percentile0.0010194824
Q10.0034493641
median0.0073460839
Q30.018189365
95-th percentile0.12091181
Maximum0.9574104
Range0.95718818
Interquartile range (IQR)0.014740001

Descriptive statistics

Standard deviation0.091606699
Coefficient of variation (CV)2.97778
Kurtosis46.042634
Mean0.03076342
Median Absolute Deviation (MAD)0.0049794195
Skewness6.3421215
Sum2840.2943
Variance0.0083917873
MonotonicityNot monotonic
2023-07-10T14:23:25.275172image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0005284937215 2809
 
3.0%
0.013960029 100
 
0.1%
0.02956123091 100
 
0.1%
0.05878283828 100
 
0.1%
0.002044005552 97
 
0.1%
0.002758989111 97
 
0.1%
0.004765410908 97
 
0.1%
0.01730424538 96
 
0.1%
0.004609968048 95
 
0.1%
0.01445589494 89
 
0.1%
Other values (4716) 88647
96.0%
ValueCountFrequency (%)
0.0002222132753 19
< 0.1%
0.0002638197038 20
< 0.1%
0.000349583861 46
< 0.1%
0.0003496713762 15
 
< 0.1%
0.0003763197165 20
< 0.1%
0.000382441387 28
< 0.1%
0.0003988528624 17
 
< 0.1%
0.0004341393942 20
< 0.1%
0.0004390591639 15
 
< 0.1%
0.0004500276409 17
 
< 0.1%
ValueCountFrequency (%)
0.9574103951 18
< 0.1%
0.9380022883 20
< 0.1%
0.9356879592 18
< 0.1%
0.9325274825 20
< 0.1%
0.9136560559 15
< 0.1%
0.9129751325 19
< 0.1%
0.8991281986 15
< 0.1%
0.8915641904 22
< 0.1%
0.8778240681 20
< 0.1%
0.8775347471 11
< 0.1%

disappointment
Real number (ℝ)

Distinct4727
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.052717017
Minimum0.00040975744
Maximum0.97090688
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:25.351003image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00040975744
5-th percentile0.0011833712
Q10.0042243605
median0.012385983
Q30.04996662
95-th percentile0.24425926
Maximum0.97090688
Range0.97049713
Interquartile range (IQR)0.045742259

Descriptive statistics

Standard deviation0.1060136
Coefficient of variation (CV)2.0109939
Kurtosis20.771676
Mean0.052717017
Median Absolute Deviation (MAD)0.01000385
Skewness4.0629084
Sum4867.2041
Variance0.011238883
MonotonicityNot monotonic
2023-07-10T14:23:25.524587image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.000409757442 2809
 
3.0%
0.003044190467 100
 
0.1%
0.008086278802 100
 
0.1%
0.005571489804 100
 
0.1%
0.0101000123 97
 
0.1%
0.004250981496 97
 
0.1%
0.002857120591 97
 
0.1%
0.003908907413 96
 
0.1%
0.00691623101 95
 
0.1%
0.01773819001 89
 
0.1%
Other values (4717) 88647
96.0%
ValueCountFrequency (%)
0.000409757442 2809
3.0%
0.000539951463 20
 
< 0.1%
0.0005885100691 21
 
< 0.1%
0.0006050116499 18
 
< 0.1%
0.0006122792256 16
 
< 0.1%
0.0007161810645 19
 
< 0.1%
0.0007333639078 17
 
< 0.1%
0.0007584852283 15
 
< 0.1%
0.0007630955952 22
 
< 0.1%
0.0007695869717 20
 
< 0.1%
ValueCountFrequency (%)
0.9709068835 20
< 0.1%
0.9168020822 20
< 0.1%
0.9119700193 20
< 0.1%
0.8952433774 12
 
< 0.1%
0.8925821553 15
< 0.1%
0.8914338737 19
< 0.1%
0.8695884303 15
< 0.1%
0.8600011766 15
< 0.1%
0.8561009355 30
< 0.1%
0.8521513641 15
< 0.1%

disapproval
Real number (ℝ)

Distinct4724
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.0077475999
Minimum0.0001819397
Maximum0.92238599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:25.595849image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.0001819397
5-th percentile0.000670148
Q10.0017989306
median0.0036090792
Q30.0074218186
95-th percentile0.022718599
Maximum0.92238599
Range0.92220405
Interquartile range (IQR)0.005622888

Descriptive statistics

Standard deviation0.025298386
Coefficient of variation (CV)3.2653191
Kurtosis522.15183
Mean0.0077475999
Median Absolute Deviation (MAD)0.0022005804
Skewness19.481855
Sum715.31265
Variance0.00064000833
MonotonicityNot monotonic
2023-07-10T14:23:25.663443image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0004005855008 2809
 
3.0%
0.001979289111 100
 
0.1%
0.0107822828 100
 
0.1%
0.001957847737 100
 
0.1%
0.002037207363 97
 
0.1%
0.002555892803 97
 
0.1%
0.00100400683 97
 
0.1%
0.002811974846 96
 
0.1%
0.00166132499 95
 
0.1%
0.005383658689 89
 
0.1%
Other values (4714) 88647
96.0%
ValueCountFrequency (%)
0.0001819397003 16
< 0.1%
0.0002009754244 11
< 0.1%
0.0002956578974 15
< 0.1%
0.0003078739392 14
< 0.1%
0.000318389677 19
< 0.1%
0.0003302629339 18
< 0.1%
0.0003305930295 20
< 0.1%
0.0003359102411 20
< 0.1%
0.0003436359402 15
< 0.1%
0.0003619813651 12
< 0.1%
ValueCountFrequency (%)
0.9223859906 20
< 0.1%
0.564486444 19
< 0.1%
0.5305255055 16
< 0.1%
0.446059525 15
< 0.1%
0.4266047776 20
< 0.1%
0.3834041953 29
< 0.1%
0.3396735489 21
< 0.1%
0.3352879882 15
< 0.1%
0.3347477019 15
< 0.1%
0.3283751607 30
< 0.1%

embarrassment
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct4726
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.0039352003
Minimum0.00016184614
Maximum0.67296034
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:25.733945image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00016184614
5-th percentile0.00043564142
Q10.0010636152
median0.0020979613
Q30.0042485953
95-th percentile0.011846598
Maximum0.67296034
Range0.67279849
Interquartile range (IQR)0.0031849801

Descriptive statistics

Standard deviation0.011833393
Coefficient of variation (CV)3.0070624
Kurtosis2333.8579
Mean0.0039352003
Median Absolute Deviation (MAD)0.0012385842
Skewness42.455878
Sum363.32524
Variance0.00014002918
MonotonicityNot monotonic
2023-07-10T14:23:25.805537image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.00032436318 2809
 
3.0%
0.002103523118 100
 
0.1%
0.001258762321 100
 
0.1%
0.000944731175 100
 
0.1%
0.000874133606 97
 
0.1%
0.001154909143 97
 
0.1%
0.002160917036 97
 
0.1%
0.001156905433 96
 
0.1%
0.003142186208 95
 
0.1%
0.004785435274 89
 
0.1%
Other values (4716) 88647
96.0%
ValueCountFrequency (%)
0.0001618461392 30
< 0.1%
0.0001724210597 10
 
< 0.1%
0.0001794863783 21
< 0.1%
0.0002308381809 20
< 0.1%
0.0002330185234 21
< 0.1%
0.000245058065 15
< 0.1%
0.000246685202 18
< 0.1%
0.0002469913743 15
< 0.1%
0.0002495680528 21
< 0.1%
0.0002515992965 22
< 0.1%
ValueCountFrequency (%)
0.672960341 21
< 0.1%
0.1614204645 20
< 0.1%
0.139792949 20
< 0.1%
0.07739683241 20
< 0.1%
0.07485524565 20
< 0.1%
0.07428347319 15
< 0.1%
0.07397330552 20
< 0.1%
0.06746771932 17
< 0.1%
0.06373951584 17
< 0.1%
0.05927133188 10
< 0.1%

excitement
Real number (ℝ)

Distinct4726
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.070967401
Minimum0.00028893104
Maximum0.95534301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:25.879860image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00028893104
5-th percentile0.0017721807
Q10.0050114491
median0.012427746
Q30.045721099
95-th percentile0.41864628
Maximum0.95534301
Range0.95505408
Interquartile range (IQR)0.04070965

Descriptive statistics

Standard deviation0.1543027
Coefficient of variation (CV)2.1742758
Kurtosis11.948105
Mean0.070967401
Median Absolute Deviation (MAD)0.0094915051
Skewness3.3841593
Sum6552.2072
Variance0.023809324
MonotonicityNot monotonic
2023-07-10T14:23:25.951007image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.009054442868 2809
 
3.0%
0.5637542605 100
 
0.1%
0.5566571355 100
 
0.1%
0.1997752488 100
 
0.1%
0.128144294 97
 
0.1%
0.00520773977 97
 
0.1%
0.2070688605 97
 
0.1%
0.9426585436 96
 
0.1%
0.008427318186 95
 
0.1%
0.00663798349 89
 
0.1%
Other values (4716) 88647
96.0%
ValueCountFrequency (%)
0.0002889310417 19
< 0.1%
0.0003048433864 16
< 0.1%
0.0003574412549 20
< 0.1%
0.0003700523521 18
< 0.1%
0.0004238410911 13
< 0.1%
0.000477526919 15
< 0.1%
0.0005008053849 17
< 0.1%
0.0005024725106 14
< 0.1%
0.0005086876336 15
< 0.1%
0.0005345399841 13
< 0.1%
ValueCountFrequency (%)
0.955343008 15
 
< 0.1%
0.9522784948 30
 
< 0.1%
0.9492473602 19
 
< 0.1%
0.9475292563 14
 
< 0.1%
0.9446265697 20
 
< 0.1%
0.9426585436 96
0.1%
0.940926671 16
 
< 0.1%
0.9408245683 14
 
< 0.1%
0.9408015609 30
 
< 0.1%
0.939243257 20
 
< 0.1%

fear
Real number (ℝ)

Distinct4725
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.012941196
Minimum0.00025264855
Maximum0.7810604
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:26.024952image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00025264855
5-th percentile0.00064947474
Q10.0020213451
median0.0046254438
Q30.010527462
95-th percentile0.044049781
Maximum0.7810604
Range0.78080775
Interquartile range (IQR)0.0085061167

Descriptive statistics

Standard deviation0.039001474
Coefficient of variation (CV)3.0137458
Kurtosis144.38586
Mean0.012941196
Median Absolute Deviation (MAD)0.0031790533
Skewness10.53491
Sum1194.8218
Variance0.0015211149
MonotonicityNot monotonic
2023-07-10T14:23:26.098224image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0003436184197 2809
 
3.0%
0.005073006731 100
 
0.1%
0.002179724397 100
 
0.1%
0.02548020333 100
 
0.1%
0.005433652084 97
 
0.1%
0.002687053522 97
 
0.1%
0.001108974218 97
 
0.1%
0.00188082736 96
 
0.1%
0.002478365786 95
 
0.1%
0.01224938966 89
 
0.1%
Other values (4715) 88647
96.0%
ValueCountFrequency (%)
0.0002526485478 30
< 0.1%
0.0002537010005 20
< 0.1%
0.0002588303178 25
< 0.1%
0.0002645141212 25
< 0.1%
0.0002735038579 15
 
< 0.1%
0.0002870581811 20
< 0.1%
0.000294210593 17
 
< 0.1%
0.0002953564399 46
< 0.1%
0.0003068808292 21
< 0.1%
0.000307449518 20
< 0.1%
ValueCountFrequency (%)
0.7810603976 19
< 0.1%
0.707454145 17
< 0.1%
0.7010254264 15
< 0.1%
0.666562736 25
< 0.1%
0.5628036261 20
< 0.1%
0.548838973 30
< 0.1%
0.5418248773 14
< 0.1%
0.5167623758 19
< 0.1%
0.4945044816 20
< 0.1%
0.4928394258 12
 
< 0.1%

gratitude
Real number (ℝ)

Distinct4727
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.023211124
Minimum4.695548 × 10-5
Maximum0.99648201
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:26.174329image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum4.695548 × 10-5
5-th percentile0.00027313095
Q10.000765623
median0.0016145656
Q30.0045853262
95-th percentile0.04741291
Maximum0.99648201
Range0.99643506
Interquartile range (IQR)0.0038197032

Descriptive statistics

Standard deviation0.11476789
Coefficient of variation (CV)4.944521
Kurtosis48.582441
Mean0.023211124
Median Absolute Deviation (MAD)0.0011313259
Skewness6.8797649
Sum2143.0134
Variance0.013171669
MonotonicityNot monotonic
2023-07-10T14:23:26.245762image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001542964601 2809
 
3.0%
0.0035627631 100
 
0.1%
0.0005178957945 100
 
0.1%
0.003657955211 100
 
0.1%
0.0009349599131 97
 
0.1%
0.003799902974 97
 
0.1%
0.004337762017 97
 
0.1%
0.006962097716 96
 
0.1%
0.001760853454 95
 
0.1%
0.0007473781588 89
 
0.1%
Other values (4717) 88647
96.0%
ValueCountFrequency (%)
4.695547977 × 10-529
< 0.1%
4.77780959 × 10-515
< 0.1%
5.976777538 × 10-518
< 0.1%
6.926534843 × 10-517
< 0.1%
7.082793309 × 10-527
< 0.1%
7.94176085 × 10-520
< 0.1%
8.176760457 × 10-520
< 0.1%
8.479866665 × 10-520
< 0.1%
8.749740664 × 10-520
< 0.1%
8.867064753 × 10-517
< 0.1%
ValueCountFrequency (%)
0.9964820147 20
< 0.1%
0.9963633418 20
< 0.1%
0.9958686829 11
 
< 0.1%
0.9942135215 30
< 0.1%
0.9918497801 17
< 0.1%
0.9894046783 20
< 0.1%
0.9887443781 20
< 0.1%
0.9883610606 20
< 0.1%
0.9879361987 20
< 0.1%
0.9876121879 14
< 0.1%

joy
Real number (ℝ)

Distinct4727
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.23937419
Minimum0.00068786868
Maximum1.6543745
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:26.316956image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00068786868
5-th percentile0.0084171882
Q10.028984584
median0.10040951
Q30.35464071
95-th percentile0.87689232
Maximum1.6543745
Range1.6536867
Interquartile range (IQR)0.32565612

Descriptive statistics

Standard deviation0.2894348
Coefficient of variation (CV)1.2091312
Kurtosis1.3790571
Mean0.23937419
Median Absolute Deviation (MAD)0.084093555
Skewness1.4554553
Sum22100.701
Variance0.083772501
MonotonicityNot monotonic
2023-07-10T14:23:26.386494image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01688753208 2809
 
3.0%
0.7927992954 100
 
0.1%
0.3706976296 100
 
0.1%
0.1001595533 100
 
0.1%
0.2439599028 97
 
0.1%
0.003320651711 97
 
0.1%
0.1744449928 97
 
0.1%
0.1496800389 96
 
0.1%
0.007699634414 95
 
0.1%
0.110510991 89
 
0.1%
Other values (4717) 88647
96.0%
ValueCountFrequency (%)
0.0006878686836 29
< 0.1%
0.0007813438133 17
< 0.1%
0.0008928416792 28
< 0.1%
0.000936872384 19
< 0.1%
0.00106261333 20
< 0.1%
0.001245162857 28
< 0.1%
0.001287915191 13
< 0.1%
0.001309142535 21
< 0.1%
0.001375217631 30
< 0.1%
0.001391035184 20
< 0.1%
ValueCountFrequency (%)
1.65437454 20
< 0.1%
1.578695178 15
< 0.1%
1.570110559 15
< 0.1%
1.570024431 15
< 0.1%
1.550870061 16
< 0.1%
1.51560694 17
< 0.1%
1.49964422 10
< 0.1%
1.497996688 20
< 0.1%
1.475130618 19
< 0.1%
1.467563152 19
< 0.1%

love
Real number (ℝ)

Distinct4726
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.2197904
Minimum0.00040200248
Maximum0.99513513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:26.460253image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00040200248
5-th percentile0.002816028
Q10.018521171
median0.069925092
Q30.31717294
95-th percentile0.90712816
Maximum0.99513513
Range0.99473313
Interquartile range (IQR)0.29865177

Descriptive statistics

Standard deviation0.29196536
Coefficient of variation (CV)1.3283808
Kurtosis0.6574821
Mean0.2197904
Median Absolute Deviation (MAD)0.062355302
Skewness1.417968
Sum20292.588
Variance0.085243769
MonotonicityNot monotonic
2023-07-10T14:23:26.532983image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.002195975743 2809
 
3.0%
0.06228217483 100
 
0.1%
0.2436284721 100
 
0.1%
0.02127908729 100
 
0.1%
0.1190503016 97
 
0.1%
0.4161707759 97
 
0.1%
0.1986688524 97
 
0.1%
0.04473337159 96
 
0.1%
0.02246527188 95
 
0.1%
0.712346375 89
 
0.1%
Other values (4716) 88647
96.0%
ValueCountFrequency (%)
0.0004020024789 29
< 0.1%
0.0004816522414 17
< 0.1%
0.0005037008086 17
< 0.1%
0.000527860655 18
< 0.1%
0.0005498632672 20
< 0.1%
0.000559588545 16
< 0.1%
0.000591290358 9
 
< 0.1%
0.0006030405639 19
< 0.1%
0.0006044025649 13
< 0.1%
0.0006061464665 19
< 0.1%
ValueCountFrequency (%)
0.9951351285 20
< 0.1%
0.993547976 18
< 0.1%
0.9926128387 16
< 0.1%
0.9923256636 19
< 0.1%
0.9915607572 15
< 0.1%
0.9908701777 20
< 0.1%
0.990655005 17
< 0.1%
0.9904744029 20
< 0.1%
0.9901948571 15
< 0.1%
0.9899165034 20
< 0.1%

optimism
Real number (ℝ)

Distinct4726
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.081259421
Minimum0.00029712275
Maximum0.98540074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:26.609941image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00029712275
5-th percentile0.0011847037
Q10.0059685777
median0.015702058
Q30.057449382
95-th percentile0.4659887
Maximum0.98540074
Range0.98510361
Interquartile range (IQR)0.051480804

Descriptive statistics

Standard deviation0.16877148
Coefficient of variation (CV)2.0769466
Kurtosis10.556143
Mean0.081259421
Median Absolute Deviation (MAD)0.012572976
Skewness3.2131792
Sum7502.4386
Variance0.028483813
MonotonicityNot monotonic
2023-07-10T14:23:26.680510image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001184703666 2809
 
3.0%
0.05610178411 100
 
0.1%
0.0574493818 100
 
0.1%
0.002752159722 100
 
0.1%
0.0007504276582 97
 
0.1%
0.003806041554 97
 
0.1%
0.01936688088 97
 
0.1%
0.003199410159 96
 
0.1%
0.07457503676 95
 
0.1%
0.1063293591 89
 
0.1%
Other values (4716) 88647
96.0%
ValueCountFrequency (%)
0.0002971227514 17
< 0.1%
0.0003032129607 13
< 0.1%
0.0003220429644 17
< 0.1%
0.0003287697909 20
< 0.1%
0.0003934924898 16
< 0.1%
0.000406332314 17
< 0.1%
0.0004325848713 15
< 0.1%
0.0004550507874 20
< 0.1%
0.00048283246 20
< 0.1%
0.0004874722217 20
< 0.1%
ValueCountFrequency (%)
0.9854007363 18
< 0.1%
0.9817113876 15
< 0.1%
0.9797018766 24
< 0.1%
0.9796756506 25
< 0.1%
0.9737606049 15
< 0.1%
0.9731754661 25
< 0.1%
0.9692676067 15
< 0.1%
0.9652010798 15
< 0.1%
0.9606567025 15
< 0.1%
0.9593273997 18
< 0.1%

pride
Real number (ℝ)

Distinct4724
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.0037812456
Minimum9.178403 × 10-5
Maximum0.10122461
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:26.754600image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum9.178403 × 10-5
5-th percentile0.00059903035
Q10.001459207
median0.0025699963
Q30.004719995
95-th percentile0.010863487
Maximum0.10122461
Range0.10113282
Interquartile range (IQR)0.0032607879

Descriptive statistics

Standard deviation0.004234273
Coefficient of variation (CV)1.119809
Kurtosis101.92593
Mean0.0037812456
Median Absolute Deviation (MAD)0.0014011362
Skewness6.4812962
Sum349.11107
Variance1.7929068 × 10-5
MonotonicityNot monotonic
2023-07-10T14:23:26.826793image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001459207037 2809
 
3.0%
0.001279487857 100
 
0.1%
0.004861282185 100
 
0.1%
0.007065614685 100
 
0.1%
0.001486919704 97
 
0.1%
0.003274882445 97
 
0.1%
0.006748555694 97
 
0.1%
0.004786171485 96
 
0.1%
0.003348320723 95
 
0.1%
0.002456479473 89
 
0.1%
Other values (4714) 88647
96.0%
ValueCountFrequency (%)
9.178402979 × 10-520
< 0.1%
0.0001174208883 17
< 0.1%
0.0001414109429 21
< 0.1%
0.0001450139971 19
< 0.1%
0.0001457998587 19
< 0.1%
0.0001651114144 30
< 0.1%
0.0001705802424 17
< 0.1%
0.0001746560447 11
 
< 0.1%
0.0001747644856 20
< 0.1%
0.0001781048049 15
< 0.1%
ValueCountFrequency (%)
0.1012246087 25
< 0.1%
0.07758509368 17
 
< 0.1%
0.04920675978 14
 
< 0.1%
0.03700798005 21
< 0.1%
0.03666116297 12
 
< 0.1%
0.03520977497 49
0.1%
0.03297793493 15
 
< 0.1%
0.03198522329 14
 
< 0.1%
0.03016219474 15
 
< 0.1%
0.02979336306 15
 
< 0.1%

realization
Real number (ℝ)

Distinct4726
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.056920579
Minimum0.00050159078
Maximum0.96944439
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:26.897678image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00050159078
5-th percentile0.0022990874
Q10.0069887587
median0.017371774
Q30.050552718
95-th percentile0.25194234
Maximum0.96944439
Range0.9689428
Interquartile range (IQR)0.04356396

Descriptive statistics

Standard deviation0.11104123
Coefficient of variation (CV)1.9508099
Kurtosis19.935721
Mean0.056920579
Median Absolute Deviation (MAD)0.013308411
Skewness4.0524183
Sum5255.3063
Variance0.012330155
MonotonicityNot monotonic
2023-07-10T14:23:26.968301image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.002299087355 2809
 
3.0%
0.01528997719 100
 
0.1%
0.00393194519 100
 
0.1%
0.02196298353 100
 
0.1%
0.03956532478 97
 
0.1%
0.009666628204 97
 
0.1%
0.03225332871 97
 
0.1%
0.007425050717 96
 
0.1%
0.09453177452 95
 
0.1%
0.04585359991 89
 
0.1%
Other values (4716) 88647
96.0%
ValueCountFrequency (%)
0.0005015907809 15
< 0.1%
0.0006873341044 17
< 0.1%
0.0007040465716 26
< 0.1%
0.0008123170701 15
< 0.1%
0.0008440107922 30
< 0.1%
0.0008858715883 15
< 0.1%
0.0009078259463 17
< 0.1%
0.000956494885 19
< 0.1%
0.0009577240562 22
< 0.1%
0.0009983363561 15
< 0.1%
ValueCountFrequency (%)
0.9694443941 20
< 0.1%
0.9680709839 13
< 0.1%
0.9564858675 20
< 0.1%
0.9293143153 19
< 0.1%
0.9203257561 16
< 0.1%
0.9002056718 15
< 0.1%
0.8832881451 20
< 0.1%
0.8713305593 14
< 0.1%
0.8654145002 29
< 0.1%
0.8628547788 15
< 0.1%

relief
Real number (ℝ)

Distinct4726
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.0205457
Minimum0.00020999339
Maximum0.41526935
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:27.156829image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00020999339
5-th percentile0.00087424484
Q10.0025656498
median0.0074380403
Q30.021981172
95-th percentile0.085491091
Maximum0.41526935
Range0.41505935
Interquartile range (IQR)0.019415522

Descriptive statistics

Standard deviation0.035050466
Coefficient of variation (CV)1.7059758
Kurtosis21.158957
Mean0.0205457
Median Absolute Deviation (MAD)0.0060567065
Skewness3.8481398
Sum1896.9228
Variance0.0012285352
MonotonicityNot monotonic
2023-07-10T14:23:27.223005image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.001012650202 2809
 
3.0%
0.01203495823 100
 
0.1%
0.0307034459 100
 
0.1%
0.006926370319 100
 
0.1%
0.00903124921 97
 
0.1%
0.01413019653 97
 
0.1%
0.001028129132 97
 
0.1%
0.004050632939 96
 
0.1%
0.005351884756 95
 
0.1%
0.006204278674 89
 
0.1%
Other values (4716) 88647
96.0%
ValueCountFrequency (%)
0.0002099933918 20
< 0.1%
0.0002167167258 20
< 0.1%
0.0002221065224 11
< 0.1%
0.0002650331298 15
< 0.1%
0.0002658979793 17
< 0.1%
0.0002694460272 20
< 0.1%
0.0002756562608 25
< 0.1%
0.0002824568073 15
< 0.1%
0.000293179357 20
< 0.1%
0.0003061137686 20
< 0.1%
ValueCountFrequency (%)
0.415269345 20
< 0.1%
0.3831172884 24
< 0.1%
0.3531891704 15
< 0.1%
0.348062396 18
< 0.1%
0.3208880424 19
< 0.1%
0.3100621104 18
< 0.1%
0.2823242545 20
< 0.1%
0.2777034044 15
< 0.1%
0.2758839428 14
< 0.1%
0.2618840933 20
< 0.1%

sadness
Real number (ℝ)

Distinct4727
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.22159928
Minimum0.00046836281
Maximum1.1618197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:27.292037image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00046836281
5-th percentile0.0020834469
Q10.011040865
median0.045283196
Q30.31182186
95-th percentile0.97453349
Maximum1.1618197
Range1.1613513
Interquartile range (IQR)0.30078099

Descriptive statistics

Standard deviation0.31948246
Coefficient of variation (CV)1.4417125
Kurtosis0.68281068
Mean0.22159928
Median Absolute Deviation (MAD)0.041366464
Skewness1.4507005
Sum20459.597
Variance0.10206904
MonotonicityNot monotonic
2023-07-10T14:23:27.364815image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0005870359601 2809
 
3.0%
0.01344907284 100
 
0.1%
0.02508475468 100
 
0.1%
0.01152086118 100
 
0.1%
0.05392360128 97
 
0.1%
0.004093505617 97
 
0.1%
0.005511811236 97
 
0.1%
0.002908404509 96
 
0.1%
0.01860861341 95
 
0.1%
0.1819139281 89
 
0.1%
Other values (4717) 88647
96.0%
ValueCountFrequency (%)
0.0004683628067 16
 
< 0.1%
0.0005038786767 23
 
< 0.1%
0.0005870359601 2809
3.0%
0.0006585841038 15
 
< 0.1%
0.0007021948404 20
 
< 0.1%
0.0007121583476 20
 
< 0.1%
0.000748094244 20
 
< 0.1%
0.0007504655514 16
 
< 0.1%
0.0007696504763 46
 
< 0.1%
0.0008013112238 30
 
< 0.1%
ValueCountFrequency (%)
1.161819652 20
< 0.1%
1.159601003 22
< 0.1%
1.137854666 18
< 0.1%
1.123116121 25
< 0.1%
1.116987258 15
< 0.1%
1.112370953 20
< 0.1%
1.108017772 20
< 0.1%
1.107550785 15
< 0.1%
1.101966023 20
< 0.1%
1.10153617 20
< 0.1%

neutral
Real number (ℝ)

Distinct4724
Distinct (%)5.1%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean0.092194854
Minimum0.00053680723
Maximum0.99285406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size721.4 KiB
2023-07-10T14:23:27.443006image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Quantile statistics

Minimum0.00053680723
5-th percentile0.0021639955
Q10.0047363215
median0.0095134452
Q30.02935336
95-th percentile0.85882038
Maximum0.99285406
Range0.99231725
Interquartile range (IQR)0.024617038

Descriptive statistics

Standard deviation0.22902384
Coefficient of variation (CV)2.4841282
Kurtosis7.5978955
Mean0.092194854
Median Absolute Deviation (MAD)0.0061987012
Skewness2.9863096
Sum8512.0743
Variance0.052451918
MonotonicityNot monotonic
2023-07-10T14:23:27.513258image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9266286492 2809
 
3.0%
0.01698680595 100
 
0.1%
0.01145894639 100
 
0.1%
0.005407043733 100
 
0.1%
0.05837415531 97
 
0.1%
0.01843520813 97
 
0.1%
0.007503972854 97
 
0.1%
0.008291983046 96
 
0.1%
0.04002555832 95
 
0.1%
0.009526260197 89
 
0.1%
Other values (4714) 88647
96.0%
ValueCountFrequency (%)
0.0005368072307 20
< 0.1%
0.0005886124563 20
< 0.1%
0.0007182035479 20
< 0.1%
0.0007687184261 20
< 0.1%
0.0008271469851 19
< 0.1%
0.0008682684274 15
< 0.1%
0.0008712294511 17
< 0.1%
0.0008726414526 19
< 0.1%
0.0008758748882 14
< 0.1%
0.0008791110013 20
< 0.1%
ValueCountFrequency (%)
0.9928540587 17
< 0.1%
0.992043674 19
< 0.1%
0.9916316867 20
< 0.1%
0.9912261367 30
< 0.1%
0.9904685616 15
< 0.1%
0.9902065396 20
< 0.1%
0.9899781942 20
< 0.1%
0.98995471 15
< 0.1%
0.9874988198 21
< 0.1%
0.987300992 19
< 0.1%

Interactions

2023-07-10T14:23:21.402660image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:50.576510image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:52.103586image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:53.569211image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:54.999035image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:56.534005image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:57.931888image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:59.437222image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:00.852820image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:02.258285image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:03.799428image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:05.184022image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:06.794309image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:08.191777image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:09.680987image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:11.206865image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:12.644138image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:14.144099image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:15.547167image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:16.969814image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:18.474795image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:19.862308image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:21.464934image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:50.652050image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:52.172781image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:53.631397image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:55.058220image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:56.593273image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:57.995473image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:59.496480image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:00.911287image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:02.323334image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:03.856886image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:05.246485image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:06.856285image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:08.257088image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:09.745275image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:11.270050image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:12.702920image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:14.205815image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:15.615161image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:17.031864image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:18.540886image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:19.926750image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:21.532471image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:50.721611image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:52.240849image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:53.697778image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:55.135351image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:56.660107image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:58.060113image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
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2023-07-10T14:23:00.726678image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:02.131329image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:03.670297image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:05.056637image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:06.646467image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:08.063323image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:09.541007image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:11.079165image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:12.515998image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:14.017031image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:15.416985image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:16.838937image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:18.344746image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:19.731477image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:21.274118image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:22.766178image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:51.965656image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:53.505153image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:54.932977image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:56.467087image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:57.869989image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:22:59.376033image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:00.791247image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:02.194659image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:03.736299image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:05.119729image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:06.715112image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:08.127096image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:09.609917image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:11.145459image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:12.582134image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:14.080688image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:15.485108image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:16.906600image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:18.412888image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:19.799292image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
2023-07-10T14:23:21.341607image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/

Correlations

2023-07-10T14:23:27.596221image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Unnamed: 0admirationangerapprovalcaringconfusioncuriositydesiredisappointmentdisapprovalembarrassmentexcitementfeargratitudejoyloveoptimismpriderealizationreliefsadnessneutral
Unnamed: 01.0000.066-0.0500.0330.013-0.102-0.0550.024-0.094-0.058-0.0840.034-0.0800.079-0.017-0.0270.0280.058-0.0650.020-0.109-0.032
admiration0.0661.000-0.4490.444-0.176-0.357-0.244-0.061-0.420-0.325-0.2240.408-0.2240.1020.1950.0230.0670.641-0.2500.009-0.448-0.488
anger-0.050-0.4491.000-0.3580.0910.6210.3380.2950.7590.7280.693-0.2300.621-0.035-0.0410.0290.088-0.0750.3930.0920.624-0.061
approval0.0330.444-0.3581.0000.109-0.259-0.2490.007-0.184-0.126-0.0730.006-0.141-0.091-0.0460.1390.1990.2040.1340.027-0.179-0.223
caring0.013-0.1760.0910.1091.0000.2920.3140.3960.1440.317-0.050-0.0370.2920.3720.2180.0170.6460.0260.1230.6500.324-0.224
confusion-0.102-0.3570.621-0.2590.2921.0000.4900.3090.7330.7090.682-0.0840.8830.0270.100-0.0310.208-0.0700.6520.3930.671-0.058
curiosity-0.055-0.2440.338-0.2490.3140.4901.0000.3630.1860.2970.1770.3200.3990.1500.2400.1130.080-0.0270.1020.2170.218-0.129
desire0.024-0.0610.2950.0070.3960.3090.3631.0000.3020.3000.2750.2020.3770.0270.1770.4300.6550.2380.2590.1330.261-0.358
disappointment-0.094-0.4200.759-0.1840.1440.7330.1860.3021.0000.7380.842-0.3920.724-0.115-0.1260.0970.216-0.1220.6480.1460.888-0.069
disapproval-0.058-0.3250.728-0.1260.3170.7090.2970.3000.7381.0000.609-0.2850.6650.111-0.030-0.0430.328-0.0310.5150.2960.591-0.141
embarrassment-0.084-0.2240.693-0.073-0.0500.6820.1770.2750.8420.6091.000-0.2070.717-0.1520.0060.1160.1290.0790.7460.0860.713-0.122
excitement0.0340.408-0.2300.006-0.037-0.0840.3200.202-0.392-0.285-0.2071.000-0.0470.1160.6450.188-0.0340.607-0.1320.313-0.417-0.330
fear-0.080-0.2240.621-0.1410.2920.8830.3990.3770.7240.6650.717-0.0471.0000.0190.1120.0540.2380.0290.6380.3940.705-0.189
gratitude0.0790.102-0.035-0.0910.3720.0270.1500.027-0.1150.111-0.1520.1160.0191.0000.227-0.2540.3420.359-0.0140.492-0.126-0.316
joy-0.0170.195-0.041-0.0460.2180.1000.2400.177-0.126-0.0300.0060.6450.1120.2271.0000.2420.1710.4940.0300.526-0.016-0.474
love-0.0270.0230.0290.1390.017-0.0310.1130.4300.097-0.0430.1160.1880.054-0.2540.2421.0000.042-0.0480.027-0.2890.121-0.274
optimism0.0280.0670.0880.1990.6460.2080.0800.6550.2160.3280.129-0.0340.2380.3420.1710.0421.0000.3020.2370.4220.209-0.424
pride0.0580.641-0.0750.2040.026-0.070-0.0270.238-0.122-0.0310.0790.6070.0290.3590.494-0.0480.3021.0000.0800.451-0.221-0.483
realization-0.065-0.2500.3930.1340.1230.6520.1020.2590.6480.5150.746-0.1320.638-0.0140.0300.0270.2370.0801.0000.3370.506-0.052
relief0.0200.0090.0920.0270.6500.3930.2170.1330.1460.2960.0860.3130.3940.4920.526-0.2890.4220.4510.3371.0000.214-0.272
sadness-0.109-0.4480.624-0.1790.3240.6710.2180.2610.8880.5910.713-0.4170.705-0.126-0.0160.1210.209-0.2210.5060.2141.000-0.055
neutral-0.032-0.488-0.061-0.223-0.224-0.058-0.129-0.358-0.069-0.141-0.122-0.330-0.189-0.316-0.474-0.274-0.424-0.483-0.052-0.272-0.0551.000

Missing values

2023-07-10T14:23:22.885540image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-07-10T14:23:23.139014image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-07-10T14:23:23.525705image/svg+xmlMatplotlib v3.6.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Unnamed: 0titleartistadmirationangerapprovalcaringconfusioncuriositydesiredisappointmentdisapprovalembarrassmentexcitementfeargratitudejoyloveoptimismpriderealizationreliefsadnessneutral
00행복SUPER JUNIOR (슈퍼주니어)0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
11Sweety클래지콰이(Clazziquai)0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
22커피 한잔 어때? (feat. 요조)HUS(허밍어반스테레오)0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
33기분 좋은 상상여행스케치0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
44좋아요~불독맨션(Bulldogmansion)0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
55옥상달빛옥상달빛0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
66One Sweet Day장연주0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
77Sweet Dream장나라0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
88낙원 (feat. 이재훈)싸이 (PSY)0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
99키친이소은0.0071160.008560.004360.2770680.0042030.0117150.021110.0028840.0055990.0004470.0320210.0013680.0237110.7507070.010070.5755560.0036760.0019140.0276490.0105040.033037
Unnamed: 0titleartistadmirationangerapprovalcaringconfusioncuriositydesiredisappointmentdisapprovalembarrassmentexcitementfeargratitudejoyloveoptimismpriderealizationreliefsadnessneutral
9231892318Personal (Feat. Brail Watson) (Radio Edit)Jeffrey Bergmann(제프리 버그맨)0.1320270.0125580.3058460.2495390.1892590.6772390.0161130.0152260.0130370.0083770.0148030.1066230.0035530.1512860.4575010.0234140.0020040.1277570.0104750.1387100.004504
9231992319MurderFIRST0.1320270.0125580.3058460.2495390.1892590.6772390.0161130.0152260.0130370.0083770.0148030.1066230.0035530.1512860.4575010.0234140.0020040.1277570.0104750.1387100.004504
9232092320EasyCamila Cabello(카밀라 카베요)0.1320270.0125580.3058460.2495390.1892590.6772390.0161130.0152260.0130370.0083770.0148030.1066230.0035530.1512860.4575010.0234140.0020040.1277570.0104750.1387100.004504
9232192321Walking on SunshineONEGRAM(원그램)0.1320270.0125580.3058460.2495390.1892590.6772390.0161130.0152260.0130370.0083770.0148030.1066230.0035530.1512860.4575010.0234140.0020040.1277570.0104750.1387100.004504
9232292322I Told YouJames Blunt(제임스 블런트)0.1320270.0125580.3058460.2495390.1892590.6772390.0161130.0152260.0130370.0083770.0148030.1066230.0035530.1512860.4575010.0234140.0020040.1277570.0104750.1387100.004504
9232392323YouRaisa(라이사)0.1320270.0125580.3058460.2495390.1892590.6772390.0161130.0152260.0130370.0083770.0148030.1066230.0035530.1512860.4575010.0234140.0020040.1277570.0104750.1387100.004504
9232492324This ChristmasNe-Yo(니요)0.1320270.0125580.3058460.2495390.1892590.6772390.0161130.0152260.0130370.0083770.0148030.1066230.0035530.1512860.4575010.0234140.0020040.1277570.0104750.1387100.004504
9232592325Yearning For Your LovePJ Morton [Maroon 5]0.1320270.0125580.3058460.2495390.1892590.6772390.0161130.0152260.0130370.0083770.0148030.1066230.0035530.1512860.4575010.0234140.0020040.1277570.0104750.1387100.004504
9232692326Girl (You Got Me Good)Favor0.5944520.0011870.1411630.2053790.0041430.0015230.0033400.0018850.0009450.0006070.0376300.0018560.0017540.1350540.0688270.0089210.0024160.0060440.0250520.0067520.013259
9232792327Chemistry (feat. Astrid Cordes)FavNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN